Self-correcting adaptive long-stare electro-optical system

ABSTRACT

An imaging platform minimizes image distortion when there is relative motion of the imaging platform with respect to the scene being imaged where the imaging platform may be particularly susceptible to distortion when it is configured with a wide field of view or high angular rate of movement, or when performing long-stares at a given scene (e.g., for nighttime and low-light imaging.) Distortion correction may be performed by predicting distortion due to the relative motion of the imaging platform, determining optical transformations to prevent the distortion, dynamically adjusting the optics of the imaging platform during exposure, and performing digital image correction.

BACKGROUND

It is often desirable to image scenes, or subjects within a scene, whenthere is relative motion between the subject and the imaging platform. Ashort exposure period may be used when motion is present so that thesubject appears stationary for the duration of the exposure. However,underexposure and loss of contrast in the image may result.Alternatively, if longer exposure periods are used, motion induceddistortion may cause the image to blur. As a result, for example,staring time (i.e., exposure period) of space platforms may be limitedto approximately 100 ms.

It may also be possible to increase the size of the aperture of theimaging platform in order to capture more light and enable use of ashorter exposure period. However, the cost of some imaging platforms(e.g., airborne and space platforms) can scale geometrically withaperture size. As a result, users may not be able to afford imagery ofthe necessary quality.

An imaging platform having improved image quality is desired. Forexample, an imaging platform is desired which can correct distortioncaused by relative motion between the imaging platform and the scene,thereby enabling longer stare times. Further, an imaging platform isdesired which can enhance the quality of captured images in applicationswhich are particularly susceptible to distortion, e.g., imagingplatforms having a wide field of view and/or high angular rates ofmovement with respect to the ground, and low-light and nighttime imagingplatforms.

SUMMARY

According to various embodiments, an imaging platform can minimize imagedistortion (e.g., blurring) when there is relative motion of the imagingplatform with respect to the scene. In particular, airborne andlow-orbit space platforms used for ground imaging, for example, tend tobe sensitive to motion due to their wide fields of view and/or highangular rates of movement. In addition, nighttime and low-light imagingplatforms are susceptible to distortion since longer exposure periodsfor collecting light are required. By minimizing image distortion due tomotion, the exposure period can be increased to reduce underexposure andloss of contrast without causing blur. Further, an imaging platform canutilize a smaller aperture, thus reducing weight, volume, and cost.

Distortion due to changes in viewing geometry (e.g., range, elevationangle, azimuthal angle, rotation etc.) in an individual exposure or in aplurality of sub-frame exposures can be compensated for by dynamicallyadjusting optics of the imaging platform. Optical compensation can beperformed in real time and may increase staring time by a factor of10-100× (i.e., 1-10 seconds), depending on the angular extent of thefield of view (FOV). Additionally, a plurality of sub-frame exposuresmay be captured and combined into a composite image of higher quality,since more light may be received over the total duration of thesub-frame exposures.

In various embodiments, the imaging platform may comprise a variety ofsensors including staring imaging sensors, imaging Fourier transformspectrometers, instruments with two or more angles of view (such as astereo viewing system), very wide field line scanners, and long dwellOverhead Non-Imaging Infrared (ONIR) and missile warning sensors.

In an embodiment, a system is configured to capture images and comprisesan imaging platform configured to capture an image of a scene during anexposure period; a distortion prediction processor configured todetermine transformations to prevent or correct image distortion causedby relative motion between the scene and the imaging platform, and todetermine residual transformations to correct residual image distortion;a controller configured to control an optical element based on thetransformations to compensate for the image distortion; and a digitalcorrection processor configured to digitally process the image tocompensate for the residual image distortion.

In another embodiment, a method for capturing images comprises capturingan image of a scene during an exposure period with an imaging platform;determining transformations to prevent image distortion caused byrelative motion between the scene and the imaging platform; controllingan optical element based on the transformations to compensate for theimage distortion; determining residual transformations to correctresidual image distortion; and digitally processing the image tocompensate for the residual image distortion.

According to further embodiments, the transformations may be determinedbased upon the relative motion, viewing geometry, and exposure period ofthe imaging platform; the image distortion is determined based on atopographical model; a set of optical transformations representingoptical adjustments which the imaging platform is capable of performingare determined; a best fit of the transformations to minimize the imagedistortion are determined; the transformations include rotation andanamorphic focal length transformations; the controller continuouslyadjusts the optical element during an exposure period to maintain anapproximately constant alignment between the scene and the imagingplatform; a plurality of images captured during the exposure period arecombined into a composite image; the image distortion between aplurality of images captured are analyzed to determine height,elevation, or three-dimensional information associated with the scene;and a moving average of a plurality of images captured is calculated.

These and other features and advantages of the system and method will beapparent from this disclosure. It is to be understood that the summary,drawings, and detailed description are not restrictive of the scope ofthe inventive concept described herein.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A shows an imaging platform and its initial field of view;

FIG. 1B shows distortion between the initial field of view and asubsequent field of view;

FIG. 2A shows an imaging platform and its initial field of view about astaring point;

FIG. 2B shows a subsequent field of view due to rotation of the imagingplatform about the staring point;

FIG. 3A shows an imaging platform and its initial field of view;

FIG. 3B shows a change in scale of a subsequent field of view of theimaging platform due to movement of the imaging platform directly towardthe area being imaged;

FIG. 4A shows an imaging platform as both its altitude and angle fromthe zenith is reduced;

FIG. 4B shows a subsequent field of view scaled in both the X andY-directions due to the reduction in altitude and zenith angle;

FIG. 5A shows an imaging platform as it approaches the reader in adirection perpendicular to the plane of the page;

FIG. 5B shows a subsequent field of view due to skew;

FIG. 5C shows skew depicted as a vector field;

FIG. 6 shows an embodiment of a self-correcting adaptive long-stareelectro-optical system;

FIG. 7 shows distortion prediction processor according to an embodiment;

FIG. 8 shows a digital correction processor according to an embodiment;

FIG. 9 shows a vector field of an example transformation comprising arotation;

FIG. 10 shows a vector field of an example transformation comprising ananamorphic stretch in the X-direction;

FIG. 11 shows a vector field of an example of a transformationcomprising a change in range;

FIG. 12 shows a vector field of an example of a transformationcomprising an anamorphic stretch at 45° due to skew;

FIG. 13 shows an example of the worst case distortion errors in a fieldof view from a low earth orbit space platform as a function of itsviewing angles (in-track angle and cross-track angle);

FIG. 14 shows the corrected and uncorrected distortion error as afunction of the size of field of view;

FIG. 15 shows a vector field of the overall distortion of a scene viewedfor one second over a field of view of 1.6 mrad from an altitude of 600km;

FIG. 16 shows the distortion remaining after correcting for rotation;

FIG. 17 shows the distortion remaining after correcting for zoom;

FIG. 18 shows the distortion remaining after correcting for anamorphicstretch along the x-axis; and

FIG. 19 shows the distortion remaining after correcting for anamorphicstretch at 45°.

DETAILED DESCRIPTION

FIG. 1A shows imaging platform 105, having initial field of view 110,capturing images while gazing at staring point 115. An initial image issensed at initial detector points (e.g., pixels) (shown as opencircles). However, during exposure the field of view of imaging platform105 may change due to relative movement between the scene and imagingplatform 105.

FIG. 1B shows that due to the motion of imaging platform 105 asubsequent field of view 120 is not coextensive with initial field ofview 110 at a later time in the exposure, or at the time of a laterimage capture. For instance, while it is possible to align staring point115, the detector points (shown as darkened circles) are shifted withrespect to the initial detector points. As a result, an image, or acomposite image formed by combining an initial exposure and a subsequentexposure, may be blurred.

FIGS. 2A-5C show examples of physical motions which may cause imagedistortion. FIG. 2A, for example, shows initial field of view 110 asimaging platform 105 rotates about staring point 115 with velocity V.FIG. 2B shows a rotational distortion of subsequent field of view 220due to the rotation.

FIG. 3A shows initial field of view 110 as the altitude of imagingplatform 105 is reduced. FIG. 3B shows a scale distortion of subsequentfield of view 320. In this example, the change in scale is equal in boththe horizontal and vertical directions since imaging platform 105 movesdirectly toward field of view 110. However, in general, the change inscale may be different along each axis. Changes in scale of the field ofview also result in changes in the mapping of individual image pixels tothe scene.

FIG. 4A shows imaging platform 105 approaching both the zenith and thearea being imaged. FIG. 4B shows an anamorphic scale distortion ofsubsequent field of view 420. In particular, subsequent field of view420 is scaled in both the X and Y directions due to the reduction inaltitude of imaging platform 105. Further, subsequent field of view 420is scaled in the Y-direction more than in the X-direction becauseline-of-sight 425 remains perpendicular to the X-axis while angle 430changes with respect to the Y-axis due to the change in zenith angle.

FIG. 5A shows imaging platform 105 having line-of-sight 525 moving withvelocity V (i.e., approaches the reader in a direction perpendicular tothe plane of the page). FIG. 5B shows initial field of view 105 andsubsequent field of view 520 caused by skew distortion. Further, FIG. 5Cshows an alternative depiction of skew as a vector field.

FIG. 6 shows an embodiment of a Self-Correcting Adaptive Long-StareElectro-Optical System 600 (SCALES). SCALES 600 captures images of scene605 via sensor optics 610, which may comprise multiple reflective and/ortransmissive lens elements. In an embodiment, imaging platform 105 maybe provided with conventional optics 610.

The relative motion between imaging platform 105 and scene 605 can bedetermined to minimize motion, oscillation, or vibration induceddistortions. A variety of sources can provide input data 615 describingthe relative motion, viewing geometry, and exposure period of imagingplatform 105. For example, imaging platform 105 may have a predeterminedground track for imaging selected terrain. Accordingly, input data 615may comprise control data specifying the route and/or trajectory ofimaging platform 105. Input data 605 can also be provided by sensors,either alone or in combination with control data, to directly detect themotion of imaging platform 105 or the relative motion between imagingplatform 105 and scene 605. According to various embodiments, thesensors can include inertial, global positions system (GPS), imageprocessors, etc.).

Distortion prediction processor 620 analyzes input data 615 in order topredict image distortions across a field of view during a stare time.For example, distortion prediction processor 620 can calculate thedifference between the field of view of scene 605 at the start and atthe end of each exposure period. According to various embodiments, theexposure period and the size of the field of view of imaging platform105 may be considered in determining distortion since the degree ofdistortion is approximately proportional to these factors.

Distortion prediction processor 620 can also adjust its predictionsaccording to various models describing the topography of scene 605. Forexample, distortion prediction processor 620 can utilize planar,spherical, or oblate earth models, relief or topographic models, 3Dmodels of man-made objects, and/or terrain elevation maps. For example,in one embodiment, imaging platform 105 may use a WGS-84 oblate Earthmodel.

After determining the nature and degree of distortion, distortionprediction processor 620 can determine a set of separable “Eigen”transformations which mathematically describe the distortions. EachEigen function is directly translatable into an optical adjustment forpreventing the image distortion. According to various embodiments, theEigen transformations may comprise six or fewer separabletransformations and/or may include Zernike polynomials.

For example, the Eigen transformations may comprise rotation, zoom,anamorphic stretch in azimuth (or X-axis of the focal plane assembly),anamorphic stretch at 45° (from X-axis), anamorphic stretch in elevation(Y-axis), and/or anamorphic stretch at −45° (from X-axis). According tovarious embodiments, additional or alternative transformations may beused. In particular, for example, a space platform may use rotation,anamorphic stretch in azimuth, zoom, and anamorphic stretch at 45° (fromX-axis) to correct distortion.

To maximize the degree of distortion prevention, the best fit of thetransformations can be determined according to various methods. Forexample, the best fit may be calculated using mean-square error (MSE)over the field of view, a measure of error over a portion of the fieldof view, or by minimizing the maximum error.

After the best fits are determined, transformations 625 are convertedinto commands 635 to control counter distortion optics 640. Commands 635indicate the optical adjustments which must be implemented to correctfor the distortion.

According to various embodiments, controller 630 can continuously varycounter distortion optics 640 during an exposure period. For example,counter distortion optics 640 may continuously rotate scene 605 and/orchange the effective focal length of imaging platform 105 along one ormore axes. They can include, for example, one or more zoom lenses,variable optics, spatial light modulators, or deformable mirrors.Solid-state actuators and/or Micro-Electro-Mechanical Systems (MEMS) mayalso be used, rather than motors, to limit the number of moving partswhich may be failure prone. Additionally, some transformations (e.g.,rotation) can be implemented by reorienting imaging platform 105 itself,rather than (or in addition to) adjusting counter distortion optics 640.

For example, a space platform may suffer primarily from rotationaldistortion (except for views near the flight path), which may becorrected with optics 640 by implementing a counter rotationaltransformation 625. The remaining distortions may be modeled as a changein focal length along one or more axes, which may be corrected bychanging the focal length of imaging platform 105. For instance, thefocal length may be changed by a small fraction (approximately 1% orless) of the total focal length.

Images of scene 605, as modified by distortion prevention optics 640,are focused on focal plane assembly 645. Conventional imaging platforms,in contrast, directly focus scene 605 onto focal plane assembly 645without compensating for changes in the field of view which occur duringan exposure period.

According to an embodiment, focal plane assembly 645 reads out a singleframe during each staring time. In a further embodiment multiplesub-frames are read out during each staring time so that additionaldigital correction and/or comparison may be used to combine thesub-frames. In a further embodiment, multiple sub-frames are outputtedby focal plane assembly 645 during each staring time using Fowlersampling or another non-destructive readout method, for example. Bycombining (e.g., integrating) multiple sub-frames 655, a high-qualitycomposite image 665 can be generated.

Residual distortion remaining after optical correction 640 may beremoved by digital correction processor 655. Residual distortion may bepresent if controller 630 cannot flawlessly adjust counter distortionoptics 640, or if imperfections exist for which counter distortionoptics 640 cannot correct.

In an embodiment, distortion prevention optics 640 and digitalcorrection processor 655 cooperate to correct distortion and increasethe signal-to-noise ratio of frames/sub-frames 650. In an embodiment,the relative proportion of distortion correction provided by counterdistortion optics 640 and digital correction processor 655 may varybetween 0% and 100%.

To determine the type and degree of digital distortion correctionnecessary, an error signal is provided to digital correction processor655. The error signal can comprise residual transformations orpixel-by-pixel motions 660. In particular, the difference between idealtransforms “as commanded” by controller 630 and “as executed” bydistortion prevention optics 640 can be indicated by residualtransformations 660. Further, the difference between a particularstaring “as commanded” and “as executed” can be indicated bypixel-by-pixel motions 660. Accordingly, in an embodiment, the residualdistortion in a field of view can be corrected via image processing orby resampling focal plane assembly 645. As a result, distortion in image665 caused prior to and/or during image capture can be reduced bycounter distortion optics 640, and distortion caused during and/or afterimage capture can be reduced by digital correction processor 655.

According to various embodiments, the processes described can beimplemented with a variety of microprocessors and/or software. Further,distortion prediction processor 620 and/or digital correction processor665 can be implemented off-site of imaging platform 105 (e.g., at aground location physically separated from imaging platform 105). Forexample, distortion prediction processor 620 and/or digital correctionprocessor 665 may each be implemented in multiple processors.

FIG. 7 shows an embodiment of distortion prediction processor 620, whichcan receive input data 615 indicating the relative motion, viewinggeometry, and/or exposure period of imaging platform 105. Based on inputdata 615, image distortion can be predicted by calculating thedifference between initial and subsequent fields of view 710 during astare time. Further, the prediction may be adjusted based on varioustopographical models.

The distortion between the initial and subsequent fields of view aremodeled by transformations 715 (e.g., Eigen transformations).Transformations 715 can describe a set of optical adjustments which arecapable of compensating for image distortion and are also implementableby distortion prevention optics 640. In particular, they may compriserotation, zoom, anamorphic stretch in azimuth (or X-axis of the focalplane assembly), anamorphic stretch at 45° (from X-axis), anamorphicstretch in elevation (Y-axis), and/or anamorphic stretch at −45° (fromX-axis). In order to maximize distortion prevention, transformations 715can be optimized by calculating best fits 720 to minimize mean-squareerror or the maximum error, for example. After calculating best fits720, transformations 625 (e.g., Zernike polynomials) describing opticaladjustments for correcting image distortion are outputted by distortionprediction processor 620.

In addition, residual error is calculated 730 based on the differencebetween the ideal distortion correction and the correction actuallyimplemented by distortion prevention optics 640. Residual error can berepresented by transformations or pixel-by-pixel motions 660. Commoncauses of residual error may include inaccuracies in controlling counterdistortion optics 640, or higher order aberrations for which counterdistortion optics 640 cannot correct.

FIG. 8 shows digital correction processor 620, which can further reduceimage distortion using residual error 730. Residual error 660 can beaccumulated over time by updating residual pixel errors and/ortransformations 805. Block 805 estimates the ideal pixel-by-pixeldistortion corrections and compares them to what has been implemented inthe distortion prevention optics to determine any residual distortions.Thereafter, sub-frames 650 can be resampled 810 to remove the residualdistortions at each pixel. Sub-frames 650, however, may not be alignedsuch that pixels of scene 605 correspond between frames. Accordingly,registration and warping of sub-frames 650 may be performed to spatiallyalign multiple sub-frames 650.

Sub-frames 650 can be processed in various imaging modes to generateimages 665. For example, in an embodiment, multiple sub-frames 650 canbe combined into composite image 665 to maximize signal to noise ratio.In particular, a time sequence of composite images 650 can be created byoutputting a moving average of sub-frames 650, or sub-frames 650 can besuperimposed, to create a higher quality 2D image 825. Any residualerrors 830 remaining after optical counter distortion 640 and digitalcorrection 655 may also be outputted for additional distortioncorrection or image analysis.

In a further embodiment, moving targets 840 may be detected withindistortion corrected imagery by determining the difference betweenmultiple frames 835 and detecting pixels and/or edges which move. Inaddition, object relief can be computed 845 to create 3D images 850 ofscene 605 by analyzing apparent pixel movement. For example, a series ofimages may be captured by imaging platform 105 crossing over a mountainpeak. The mountain peak may appear to move between the images (evenafter distortion correction is performed) due to parallax caused by theelevation of the mountain peak. The apparent motion of the mountain peakcan be analyzed to track pixels and edges and to calculate height byusing stereo processing techniques.

FIGS. 9-12 show vector fields associated with various transformationsfor correcting image distortion. In particular, they illustraterotation, anamorphic stretch in the X-direction, a change in focallength, and anamorphic stretch at 45°, respectively.

FIG. 13 shows an example of the uncorrected maximum distortion errorsfor imaging platform 105 having a one milliradian field of view at analtitude of 350 km. As can be seen, the distortion is a function of thein-track angle along the direction of movement of imaging platform 105,and the cross-track angle perpendicular to the direction of movement ofimaging platform 105. In general, the maximum distortion is relativelylow near the origin, but increases for values farther from the originand the axis.

FIG. 14 shows an example of corrected and uncorrected distortion as afunction of field of view of imaging platform 105 at an altitude of 350km. As can be seen, distortion increases with larger fields of view.

FIGS. 15-19 show an example of correcting distortion. In this example,four Eigen transformations (i.e., rotation, zoom, anamorphic stretch inx-axis, and anamorphic stretch along 45°) are performed. In addition,the best fit for each Eigen transformation is determined by minimizingthe mean-square error.

FIG. 15, in particular, shows a vector field of the overall directionand magnitude of distortion viewed by imaging platform 105 for onesecond over a field of view of 1.6 mrad (i.e., approximately one km)from an altitude of 600 km. FIG. 15 also shows that that the maximumdistortion or smear is approximately 28 grad per second. A pixel whosesubtense is one microradian would smear across 28 pixels in a one secondexposure.

According to an embodiment, it may be desirable to limit distortion to amaximum value of one-third of a pixel for an exposure or stare time inorder to provide sharp, high-resolution imagery. Thus without distortionprevention, using a focal plane assembly having at least 1000×1000pixels, the image would be smeared over as many as 17.5 pixels (sinceeach pixel has a field of view of 1.6 grad) in a 1.0 second exposure.Alternatively, it would be necessary to limit focal plane assembly 645to about 20×20 pixels or reduce the stare time to under 0.02 seconds (orsome intermediate combination thereof) to limit smear to one-third of apixel. Distortion prevention and correction, therefore, is desirable toenable larger pixel arrays and increased stare time with reduced smear.

FIG. 16 shows the remaining distortion after performing a rotationalcorrection. Removing rotation alone reduces the maximum distortion toapproximately 6.8 grad per second, thus enabling a 400×400 pixels focalplane assembly or a 0.2 second stare time for a one-third pixel maximumlevel of smear.

FIG. 17 shows the distortion remaining after correcting for zoom.Removing zoom, in addition to rotational distortions, reduces themaximum distortion to approximately 2.7 grad per second. Thus, it wouldbe possible to use a 1000×1000 pixel focal plane assembly with a staretime of 0.2 seconds.

FIG. 18 shows the distortion remaining after correcting for anamorphicstretch along the x-axis. Removing anamorphic stretch along the x-axisresults in a maximum distortion of approximately 3.8 grad per second. Inthis example, the worst case distortion increased for a small region ofthe focal plane, but the average distortion was reduced since thealgorithm minimized the average distortion at each stage.

FIG. 19 shows the distortion remaining after correcting for anamorphicstretch at 45°. Removing anamorphic stretch at 45° reduces the maximumdistortion to approximately 0.015 grad per second. As a result, evenlarger focal plane assemblies or much longer stare times can be usedwhen anamorphic stretch along the x-axis and at 45° is removed.According to various embodiments, the imaging platform or user may alsoselect other combinations and sequences of the transformations describedwith respect to FIGS. 16-19. The longer stare times enable a sensor tocollect images when scene radiance is weak (e.g. moonlit areas) or tocomplete scans that require a stable image (e.g, Fourier TransformSpectrometer).

While particular embodiments of this disclosure have been described, itis understood that modifications will be apparent to those skilled inthe art without departing from the spirit of the inventive concept. Thescope of the inventive concept is not limited to the specificembodiments described herein. Other embodiments, uses, and advantageswill be apparent to those skilled in art from the specification and thepractice of the claimed invention.

1. A system configured to capture images, comprising: an imagingplatform configured to capture an image of a scene during an exposureperiod; a distortion prediction processor configured to determinetransformations to prevent image distortion caused by relative motionbetween the scene and the imaging platform, and to determine residualtransformations to correct residual image distortion; a controllerconfigured to control an optical element based on the image distortiontransformations to prevent the image distortion; and a digitalcorrection processor configured to use the residual transformations todigitally process the image to compensate for the residual imagedistortion.
 2. The system of claim 1, wherein the image distortiontransformations are determined based on a relative motion, a viewinggeometry, and an exposure period of the imaging platform.
 3. The systemof claim 1, wherein the image distortion is determined by the distortionprediction processor based on a topographical model.
 4. The system ofclaim 1, wherein a set of optical transformations representing opticaladjustments which the imaging platform is capable of performing aredetermined.
 5. The system of claim 1, wherein a best set of thetransformations to minimize the image distortion are determined by thedistortion prediction processor.
 6. The system of claim 1, wherein thetransformations comprise rotational and anamorphic focal lengthtransformations.
 7. The system of claim 1, wherein the controlleradjusts the optical element during an exposure period to maintain anapproximately constant alignment between the scene and the imagingplatform.
 8. The system of claim 7, wherein the controller continuouslyadjusts the optical element during the exposure period.
 9. The system ofclaim 1, wherein a plurality of images captured during the exposureperiod are combined into a composite image by the digital correctionprocessor.
 10. The system of claim 1, wherein the image distortionbetween a plurality of images captured are analyzed by the digitalcorrection processor to determine height, elevation, orthree-dimensional information associated with the scene.
 11. The systemof claim 1, wherein a moving average of a plurality of images capturedis calculated by the digital correction processor.
 12. A method forcapturing images, the method comprising: capturing an image of a sceneduring an exposure period with an imaging platform; calculatingtransformations to prevent image distortion caused by a relative motionbetween the scene and the imaging platform; controlling an opticalelement based on the transformations to prevent the image distortion;determining residual transformations to correct residual imagedistortion; and digitally processing the image to compensate for theresidual image distortion.
 13. The method of claim 12, wherein saiddetermining image distortion is based on the relative motion, viewinggeometry, and exposure period of the imaging platform.
 14. The method ofclaim 12, wherein said determining image distortion is based on atopographical model.
 15. The method of claim 12, further comprisingdetermining a set of optical transformations representing opticaladjustments which the imaging platform is capable of performing.
 16. Themethod of claim 12, further comprising determining a best set of thetransformations to minimize the image distortion.
 17. The method ofclaim 12, wherein the image distortion transformations includerotational and anamorphic focal length transformations.
 18. The methodof claim 12, further comprising adjusting the optical element during anexposure period to maintain an approximately constant alignment betweenthe scene and the imaging platform.
 19. The method of claim 18, furthercomprising continuously adjusting the optical element during theexposure period.
 20. The method of claim 12, further comprisingcombining a plurality of images captured during the exposure period intoa composite image.
 21. The method of claim 12, further comprisinganalyzing an image distortion between a plurality of images to determineheight, elevation, or three-dimensional information associated with thescene.
 22. The method of claim 12, further comprising calculating amoving average of a plurality of images.